US adults
- Use participants’ responses (participant level) to infer factor structure (group level).
[see primary analysis]
F1 F2 F3
add_and_subtract_numbers 0.3015693 0.6612121 0.7481824
choose_what_to_do 0.6276047 0.5857757 0.7653071
feel_guilty 0.4849668 0.9023377 0.4963885
feel_happy 0.6424526 0.7481342 0.5906878
feel_love 0.5717189 0.7613585 0.6260784
feel_pain 0.8567989 0.5385989 0.5680515
- Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).
F1 F2 F3
us_adults_001_children 0.7909415 0.8954840 0.65345066
us_adults_002_dogs 0.8713361 0.5543401 0.53060180
us_adults_003_flowers 0.2746960 0.2022339 0.23657931
us_adults_004_ghosts 0.1886655 0.2927940 0.06010919
us_adults_005_god 0.5496792 0.4723938 0.83329245
us_adults_006_mice 0.8317943 0.8963377 0.73683937
X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]
[not yet done]
- Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).
- Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.
Joining, by = "subj_id"
Joining, by = "capacity"


Ghana adults
- Use participants’ responses (participant level) to infer factor structure (group level).
[see primary analysis]
F1 F2 F3
add_and_subtract_numbers 0.8977570 0.4136200 0.5320056
choose_what_to_do 0.9636416 0.4411554 0.5062167
feel_guilty 0.7126476 0.5189170 0.7807534
feel_happy 0.8540450 0.6572355 0.5245890
feel_love 0.8346477 0.6966779 0.4696541
feel_pain 0.4913013 0.9277966 0.4906321
- Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).
F1 F2 F3
gh_adults_001_mice 0.1680483 0.3503157 0.0376021
gh_adults_002_rocks 0.1338851 0.0719287 0.2601291
gh_adults_003_ghosts 0.1338851 0.0719287 0.2601291
gh_adults_004_children 0.2390378 0.6541640 0.2865854
gh_adults_005_dogs 0.2496531 0.5315998 0.1083054
gh_adults_006_mice 0.1369381 0.4771385 0.1624910
X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]
[not yet done]
- Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).
- Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.
Joining, by = "subj_id"
Joining, by = "capacity"


Thailand adults
- Use participants’ responses (participant level) to infer factor structure (group level).
[see primary analysis]
F1 F2 F3
add_and_subtract_numbers 0.3345998 0.6719092 0.7022970
choose_what_to_do 0.5664697 0.5761459 0.6567927
feel_guilty 0.5590047 0.7524198 0.5655023
feel_happy 0.6425198 0.6704252 0.6321465
feel_love 0.7073527 0.6682337 0.6099321
feel_pain 0.8593740 0.4976528 0.5549564
- Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).
F1 F2 F3
th_adults_001_beetles 0.6233860 0.1969347 0.3112682
th_adults_002_cellphones 0.4833901 0.4476217 0.6774423
th_adults_003_chickens 0.6684956 0.3701527 0.7637585
th_adults_004_children 0.5107500 0.6915550 0.6301014
th_adults_005_dogs 0.7923884 0.4644085 0.3598374
th_adults_006_flowers 0.5709171 0.7423704 0.5601472
X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]
[not yet done]
- Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).
- Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.
Joining, by = "subj_id"
Joining, by = "capacity"


China adults
- Use participants’ responses (participant level) to infer factor structure (group level).
[see primary analysis]
F1 F2 F3
add_and_subtract_numbers 0.6284769 0.3740907 0.7379231
choose_what_to_do 0.5779161 0.5186490 0.7441678
feel_guilty 0.8040457 0.3863869 0.5952617
feel_happy 0.7462067 0.6846333 0.5606633
feel_love 0.8084793 0.5283226 0.5794758
feel_pain 0.5452631 0.9016957 0.5112793
- Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).
F1 F2 F3
ch_adults_001_crickets 0.5692214 0.70389580 0.6341113
ch_adults_002_cellphones 0.1396171 0.08277301 0.2361723
ch_adults_003_chickens 0.1809178 0.75578045 0.5116998
ch_adults_004_children 0.7612876 0.76045109 0.5833485
ch_adults_005_dogs 0.7572805 0.74353491 0.2976104
ch_adults_006_flowers 0.2348517 0.46360755 0.1464597
X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]
[not yet done]
- Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).
- Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.
Joining, by = "subj_id"
Joining, by = "capacity"


Vanuatu adults
- Use participants’ responses (participant level) to infer factor structure (group level).
[see primary analysis]
F1 F2
add_and_subtract_numbers 0.8695329 0.3822839
choose_what_to_do 0.8698792 0.5049559
feel_guilty 0.6753464 0.7287989
feel_happy 0.8838876 0.4860213
feel_love 0.8311705 0.5654258
feel_pain 0.5665094 0.8688630
- Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).
F1 F2
vt_adults_001_mice 0.4745304 0.4925990
vt_adults_003_children 0.9512062 0.9196058
vt_adults_004_chickens 0.9512062 0.9196058
vt_adults_005_children 0.9512062 0.9196058
vt_adults_006_god 0.7480859 0.1696910
vt_adults_008_cellphones 0.7147565 0.9022099
X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]
[not yet done]
- Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).
- Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.
Joining, by = "subj_id"
Joining, by = "capacity"


Comparison


---
title: "R Notebook"
output: html_notebook
---


# US adults

1. Use participants' responses (participant level) to infer factor structure (group level).

[see primary analysis]

```{r}
loadings_us_adults <- efa_us_adults$loadings[] %>%
  data.frame() %>%
  rename_all(~ gsub("^.*_", "", .)) %>%
  rownames_to_column("capacity") %>%
  mutate(capacity = gsub(" \\[\\.\\.\\.\\]", "", capacity),
         capacity = gsub(" ", "_", capacity)) %>%
  column_to_rownames("capacity") %>%
  as.matrix() %>%
  # rescale to range from 0 to 1
  scales::rescale(to = c(0, 1), from = c(-1, 1))

head(loadings_us_adults)
```

2. Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).

```{r}
scores_us_adults <- efa_us_adults$scores[] %>% 
  # rescale to range from 0 to 1, using observed range of factor scores
  scales::rescale(to = c(0, 1))

head(scores_us_adults)
```

X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]

[not yet done]

3. Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).

```{r}
magic_us_adults <- magic_fun(loadings_us_adults, scores_us_adults) %>%
  data.frame()
```

4. Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.

```{r}
magic_sub_data_us_adults <- magic_us_adults - d_us_adults_w

magic_sub_data_us_adults <- magic_sub_data_us_adults %>%
  data.frame() %>%
  rownames_to_column("subj_id") %>%
  gather(capacity, diff, -subj_id) %>%
  mutate(capacity = gsub("_", " ", capacity),
         capacity = gsub("feel sick", "feel sick \\[\\.\\.\\.\\]", capacity))
```

```{r, fig.width = 4, fig.asp = 2}
magic_sub_data_us_adults %>%
  left_join(d_us_adults %>% distinct(subj_id, target)) %>%
  left_join(loadings_adults %>% 
              distinct(capacity, capacity_ord_us)) %>%
  ggplot(aes(x = capacity_ord_us, 
             y = subj_id, 
             fill = diff)) +
  facet_grid(rows = vars(target), 
             space = "free", scales = "free") +
  geom_tile() +
  scale_fill_distiller(type = "div") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1)) +
  labs(title = "US adults",
       x = "Capacity", y = "Participant", fill = "Predicted - Actual")
```

```{r}
magic_sub_data_us_adults %>%
  group_by(subj_id) %>%
  summarise(mean_diff = mean(diff, na.rm = T)) %>%
  ungroup() %>%
  ggplot(aes(x = mean_diff)) +
  geom_vline(xintercept = 0, lty = 2, color = "gray50") +
  geom_density() +
  labs(title = "US adults",
       x = "Mean Predicted - Actual", y = "Density")
```


# Ghana adults

1. Use participants' responses (participant level) to infer factor structure (group level).

[see primary analysis]

```{r}
loadings_gh_adults <- efa_gh_adults$loadings[] %>%
  data.frame() %>%
  rename_all(~ gsub("^.*_", "", .)) %>%
  rownames_to_column("capacity") %>%
  mutate(capacity = gsub(" \\[\\.\\.\\.\\]", "", capacity),
         capacity = gsub(" ", "_", capacity)) %>%
  column_to_rownames("capacity") %>%
  as.matrix() %>%
  # rescale to range from 0 to 1
  scales::rescale(to = c(0, 1), from = c(-1, 1))

head(loadings_gh_adults)
```

2. Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).

```{r}
scores_gh_adults <- efa_gh_adults$scores[] %>% 
  # rescale to range from 0 to 1, using observed range of factor scores
  scales::rescale(to = c(0, 1))

head(scores_gh_adults)
```

X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]

[not yet done]

3. Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).

```{r}
magic_gh_adults <- magic_fun(loadings_gh_adults, scores_gh_adults) %>%
  data.frame()
```

4. Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.

```{r}
magic_sub_data_gh_adults <- magic_gh_adults - d_gh_adults_w

magic_sub_data_gh_adults <- magic_sub_data_gh_adults %>%
  data.frame() %>%
  rownames_to_column("subj_id") %>%
  gather(capacity, diff, -subj_id) %>%
  mutate(capacity = gsub("_", " ", capacity),
         capacity = gsub("feel sick", "feel sick \\[\\.\\.\\.\\]", capacity))
```

```{r, fig.width = 4, fig.asp = 2}
magic_sub_data_gh_adults %>%
  left_join(d_gh_adults %>% distinct(subj_id, target)) %>%
  left_join(loadings_adults %>% 
              distinct(capacity, capacity_ord_gh)) %>%
  ggplot(aes(x = capacity_ord_gh, 
             y = subj_id, 
             fill = diff)) +
  facet_grid(rows = vars(target), 
             space = "free", scales = "free") +
  geom_tile() +
  scale_fill_distiller(type = "div") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1)) +
  labs(title = "Ghana adults",
       x = "Capacity", y = "Participant", fill = "Predicted - Actual")
```

```{r}
magic_sub_data_gh_adults %>%
  group_by(subj_id) %>%
  summarise(mean_diff = mean(diff, na.rm = T)) %>%
  ungroup() %>%
  ggplot(aes(x = mean_diff)) +
  geom_vline(xintercept = 0, lty = 2, color = "gray50") +
  geom_density() +
  labs(title = "Ghana adults",
       x = "Mean Predicted - Actual", y = "Density")
```



# Thailand adults

1. Use participants' responses (participant level) to infer factor structure (group level).

[see primary analysis]

```{r}
loadings_th_adults <- efa_th_adults$loadings[] %>%
  data.frame() %>%
  rename_all(~ gsub("^.*_", "", .)) %>%
  rownames_to_column("capacity") %>%
  mutate(capacity = gsub(" \\[\\.\\.\\.\\]", "", capacity),
         capacity = gsub(" ", "_", capacity)) %>%
  column_to_rownames("capacity") %>%
  as.matrix() %>%
  # rescale to range from 0 to 1
  scales::rescale(to = c(0, 1), from = c(-1, 1))

head(loadings_th_adults)
```

2. Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).

```{r}
scores_th_adults <- efa_th_adults$scores[] %>% 
  # rescale to range from 0 to 1, using observed range of factor scores
  scales::rescale(to = c(0, 1))

head(scores_th_adults)
```

X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]

[not yet done]

3. Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).

```{r}
magic_th_adults <- magic_fun(loadings_th_adults, scores_th_adults) %>%
  data.frame()
```

4. Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.

```{r}
magic_sub_data_th_adults <- magic_th_adults - d_th_adults_w

magic_sub_data_th_adults <- magic_sub_data_th_adults %>%
  data.frame() %>%
  rownames_to_column("subj_id") %>%
  gather(capacity, diff, -subj_id) %>%
  mutate(capacity = gsub("_", " ", capacity),
         capacity = gsub("feel sick", "feel sick \\[\\.\\.\\.\\]", capacity))
```

```{r, fig.width = 4, fig.asp = 2}
magic_sub_data_th_adults %>%
  left_join(d_th_adults %>% distinct(subj_id, target)) %>%
  left_join(loadings_adults %>% 
              distinct(capacity, capacity_ord_th)) %>%
  ggplot(aes(x = capacity_ord_th, 
             y = subj_id, 
             fill = diff)) +
  facet_grid(rows = vars(target), 
             space = "free", scales = "free") +
  geom_tile() +
  scale_fill_distiller(type = "div") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1)) +
  labs(title = "Thailand adults",
       x = "Capacity", y = "Participant", fill = "Predicted - Actual")
```

```{r}
magic_sub_data_th_adults %>%
  group_by(subj_id) %>%
  summarise(mean_diff = mean(diff, na.rm = T)) %>%
  ungroup() %>%
  ggplot(aes(x = mean_diff)) +
  geom_vline(xintercept = 0, lty = 2, color = "gray50") +
  geom_density() +
  labs(title = "Thailand adults",
       x = "Mean Predicted - Actual", y = "Density")
```


# China adults

1. Use participants' responses (participant level) to infer factor structure (group level).

[see primary analysis]

```{r}
loadings_ch_adults <- efa_ch_adults$loadings[] %>%
  data.frame() %>%
  rename_all(~ gsub("^.*_", "", .)) %>%
  rownames_to_column("capacity") %>%
  mutate(capacity = gsub(" \\[\\.\\.\\.\\]", "", capacity),
         capacity = gsub(" ", "_", capacity)) %>%
  column_to_rownames("capacity") %>%
  as.matrix() %>%
  # rescale to range from 0 to 1
  scales::rescale(to = c(0, 1), from = c(-1, 1))

head(loadings_ch_adults)
```

2. Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).

```{r}
scores_ch_adults <- efa_ch_adults$scores[] %>% 
  # rescale to range from 0 to 1, using observed range of factor scores
  scales::rescale(to = c(0, 1))

head(scores_ch_adults)
```

X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]

[not yet done]

3. Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).

```{r}
magic_ch_adults <- magic_fun(loadings_ch_adults, scores_ch_adults) %>%
  data.frame()
```

4. Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.

```{r}
magic_sub_data_ch_adults <- magic_ch_adults - d_ch_adults_w

magic_sub_data_ch_adults <- magic_sub_data_ch_adults %>%
  data.frame() %>%
  rownames_to_column("subj_id") %>%
  gather(capacity, diff, -subj_id) %>%
  mutate(capacity = gsub("_", " ", capacity),
         capacity = gsub("feel sick", "feel sick \\[\\.\\.\\.\\]", capacity))
```

```{r, fig.width = 4, fig.asp = 2}
magic_sub_data_ch_adults %>%
  left_join(d_ch_adults %>% distinct(subj_id, target)) %>%
  left_join(loadings_adults %>% 
              distinct(capacity, capacity_ord_ch)) %>%
  ggplot(aes(x = capacity_ord_ch, 
             y = subj_id, 
             fill = diff)) +
  facet_grid(rows = vars(target), 
             space = "free", scales = "free") +
  geom_tile() +
  scale_fill_distiller(type = "div") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1)) +
  labs(title = "China adults",
       x = "Capacity", y = "Participant", fill = "Predicted - Actual")
```

```{r}
magic_sub_data_ch_adults %>%
  group_by(subj_id) %>%
  summarise(mean_diff = mean(diff, na.rm = T)) %>%
  ungroup() %>%
  ggplot(aes(x = mean_diff)) +
  geom_vline(xintercept = 0, lty = 2, color = "gray50") +
  geom_density() +
  labs(title = "China adults",
       x = "Mean Predicted - Actual", y = "Density")
```


# Vanuatu adults

1. Use participants' responses (participant level) to infer factor structure (group level).

[see primary analysis]

```{r}
loadings_vt_adults <- efa_vt_adults$loadings[] %>%
  data.frame() %>%
  rename_all(~ gsub("^.*_", "", .)) %>%
  rownames_to_column("capacity") %>%
  mutate(capacity = gsub(" \\[\\.\\.\\.\\]", "", capacity),
         capacity = gsub(" ", "_", capacity)) %>%
  column_to_rownames("capacity") %>%
  as.matrix() %>%
  # rescale to range from 0 to 1
  scales::rescale(to = c(0, 1), from = c(-1, 1))

head(loadings_vt_adults)
```

2. Use factor structure (group level) in combination with responses (participant level) to generate factor scores (participant level).

```{r}
scores_vt_adults <- efa_vt_adults$scores[] %>% 
  # rescale to range from 0 to 1, using observed range of factor scores
  scales::rescale(to = c(0, 1))

head(scores_vt_adults)
```

X. Use factor scores (participant level) to make binary decisions about attributions of body, heart, and mind (participant level level). [NEEDED?]

[not yet done]

3. Use factor scores [or X?] (participant level) in combination with factor loadings (group level) to to generate likelihood of each capacity (participant level).

```{r}
magic_vt_adults <- magic_fun(loadings_vt_adults, scores_vt_adults) %>%
  data.frame()
```

4. Compare likelihood of each capacity (participant level) with actual responses (participant level) to assess consistency or violations with group-level factor structure.

```{r}
magic_sub_data_vt_adults <- magic_vt_adults - d_vt_adults_w

magic_sub_data_vt_adults <- magic_sub_data_vt_adults %>%
  data.frame() %>%
  rownames_to_column("subj_id") %>%
  gather(capacity, diff, -subj_id) %>%
  mutate(capacity = gsub("_", " ", capacity),
         capacity = gsub("feel sick", "feel sick \\[\\.\\.\\.\\]", capacity))
```

```{r, fig.width = 4, fig.asp = 2}
magic_sub_data_vt_adults %>%
  left_join(d_vt_adults %>% distinct(subj_id, target)) %>%
  left_join(loadings_adults %>% 
              distinct(capacity, capacity_ord_vt)) %>%
  ggplot(aes(x = capacity_ord_vt, 
             y = subj_id, 
             fill = diff)) +
  facet_grid(rows = vars(target), 
             space = "free", scales = "free") +
  geom_tile() +
  scale_fill_distiller(type = "div") +
  theme(axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1)) +
  labs(title = "Vanuatu adults",
       x = "Capacity", y = "Participant", fill = "Predicted - Actual")
```

```{r}
magic_sub_data_vt_adults %>%
  group_by(subj_id) %>%
  summarise(mean_diff = mean(diff, na.rm = T)) %>%
  ungroup() %>%
  ggplot(aes(x = mean_diff)) +
  geom_vline(xintercept = 0, lty = 2, color = "gray50") +
  geom_density() +
  labs(title = "Vanuatu adults",
       x = "Mean Predicted - Actual", y = "Density")
```

# Comparison

```{r}
bind_rows(magic_sub_data_us_adults,
          magic_sub_data_gh_adults,
          magic_sub_data_th_adults,
          magic_sub_data_ch_adults,
          magic_sub_data_vt_adults) %>%
  group_by(subj_id) %>%
  summarise(mean_diff = mean(diff, na.rm = T)) %>%
  ungroup() %>%
  mutate(country = gsub("_.*$", "", subj_id),
         country = factor(country,
                          levels = c("us", "gh", "th", "ch", "vt"),
                          labels = levels_country),
         target = gsub("^.*_", "", subj_id),
         target = factor(target, levels = levels_target_univ)) %>%
  ggplot(aes(x = country, y = mean_diff)) +
  geom_hline(yintercept = 0, lty = 2, color = "gray50") +
  geom_jitter(aes(color = country), height = 0, alpha = 0.5, show.legend = F) +
  geom_pointrange(data = . %>%
                    distinct(country, subj_id, mean_diff) %>%
                    group_by(country) %>%
                    multi_boot_standard(col = "mean_diff"),
                  aes(y = mean, ymin = ci_lower, ymax = ci_upper),
                  color = "black") +
  scale_color_brewer(palette = "Dark2") +
  labs(title = "All adults",
       x = "Country", y = "Mean Predicted - Actual")
```
```{r}
bind_rows(magic_sub_data_us_adults,
          magic_sub_data_gh_adults,
          magic_sub_data_th_adults,
          magic_sub_data_ch_adults,
          magic_sub_data_vt_adults) %>%
  group_by(subj_id) %>%
  summarise(mean_diff = mean(diff, na.rm = T)) %>%
  ungroup() %>%
  mutate(country = gsub("_.*$", "", subj_id),
         country = factor(country,
                          levels = c("us", "gh", "th", "ch", "vt"),
                          labels = levels_country),
         target = gsub("^.*_", "", subj_id),
         target = factor(target, levels = levels_target_univ),
         abs_mean_diff = abs(mean_diff)) %>%
  ggplot(aes(x = country, y = abs_mean_diff)) +
  geom_hline(yintercept = 0, lty = 2, color = "gray50") +
  geom_jitter(aes(color = country), height = 0, alpha = 0.5, show.legend = F) +
  geom_pointrange(data = . %>%
                    distinct(country, subj_id, abs_mean_diff) %>%
                    group_by(country) %>%
                    multi_boot_standard(col = "abs_mean_diff"),
                  aes(y = mean, ymin = ci_lower, ymax = ci_upper),
                  color = "black") +
  scale_color_brewer(palette = "Dark2") +
  labs(title = "All adults",
       x = "Country", y = "ABSOLUTE Mean Predicted - Actual")
```
